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Tel Aviv University
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Achieve surgical 3D edits without training: Prox-E lets you reshape objects with language by manipulating a compact set of geometric primitives.
Ditch the fixed trade-offs: ParetoSlider lets you smoothly navigate competing generative goals in diffusion models at inference time, without retraining.
Forget complex HDR-specific architectures: a simple log encoding and camera-aware training unlocks high-quality HDR video generation from off-the-shelf generative models.
Steer diffusion models to seamlessly blend pasted objects into new contexts without prompts by selectively loosening positional encoding constraints based on saliency.
Unleash your diffusion model's inner artist: this training-free method uses a VLM to nudge image generation away from the mundane, creating surprisingly novel visuals.
Achieve semantically coherent image compositions by mixing layout-focused and appearance-focused visual representations in a diffusion model's cross-attention.
